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Towards a Conceptual Model for Trustworthy Skills Profiles in Online Social Networks

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Abstract

For many users online profiles displaying other people’s skills are increasingly important, e.g., when contracting freelancers or finding candidates for a job opening. However, current profiles found in information systems offer either unstructured free text that is hard to handle efficiently or simplistic rating schemes that do not convey meaningful information. In addition, it is unclear how trustworthy the information on the profile is. In this paper, we propose a novel approach to online skills profiles based on users’ confirmations and the SkillRank credibility ranking and describe its prototype implementation. As spadework, we set forth six basic requirements for online skill evaluations which should generally be reflected in corresponding IS design.

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Notes

  1. 1.

    For the final release, Partuza was replaced by the social network software of our research partner.

  2. 2.

    A reasonably sized skill graph of 10,000 users with around 200,000 confirmations is computed in slightly more than one second on an average quad-core PC.

  3. 3.

    These “screenshots” have been defaced at the request of our research partner from practice, yet the fundamental concepts are unchanged.

References

  1. Bolton GE, Katok E, Ockenfels A (2004) How effective are online reputation mechanisms? An experimental investigation. Manag Sci 50(11):1587–1602

    Article  Google Scholar 

  2. Bomze I, Gutjahr W (1995) Estimating qualifications in a self-evaluating group. Qual Quan 29(3):241–250

    Article  Google Scholar 

  3. Boyd DM (2008) None of this is real: identity and participation in friendster. In: Karaganis J (ed) Structures of participation in digital culture. Social Science Research Council, New York, pp 132–157

    Google Scholar 

  4. Chen KY, Hogg T, Wozny N (2004) Experimental study of market reputation mechanisms. In: Proceedings of the 5th ACM conference on electronic commerce. ACM, New York, NY, USA, pp 234–235. doi:http://doi.acm.org/10.1145/988772.988810

  5. Cheung MY, Luo C, Sia CL, Chen H (2007) How do people evaluate electronic word-ofmouth? informational and normative based determinants of perceived credibility of online consumer recommendations in china. Proceedings of the 11th Pacific Asia conference on information systems

    Google Scholar 

  6. Conte R, Paolucci M (2002) Reputation in artificial societies: social beliefs for social order. In:Weiß G (ed) Multiagent systems, artificial societies, and simulated organizations, vol 6. Springer, New York

    Google Scholar 

  7. Dellarocas C (2001) Analyzing the economic efficiency of ebay-like online reputation reporting mechanisms. In: Proceedings of the 3rd ACM conference on electronic commerce. ACM, New York, NY, USA, pp 171–179. doi:http://doi.acm.org/10.1145/501158.501177

  8. Dellarocas C (2003) The digitization of word of mouth: promise and challenges of online feedback mechanisms. Manag Sci 49(10):1407–1424. doi:http://dx.doi.org/10. 1287/mnsc.49.10.1407.17308

    Article  Google Scholar 

  9. Efimova L (2004) Discovering the iceberg of knowledge work: a weblog case. In: Proceedings of the 5th European conference on organisational knowledge, learning and capabilities. URL https://doc.telin.nl/dscgi/ds.py/Get/File-34786/OKLC_Efimova.pdf

  10. Griffith RL, Chmielowski T, Yoshita Y (2007) Do applicants fake? An examination of the frequency of applicant faking behavior. Pers Rev 36(3):341–355. doi:http://dx.doi.org/10.1108/00483480710731310

    Article  Google Scholar 

  11. Haveliwala TH (1999) Efficient computation of pagerank. Technical report 1999-31, Stanford InfoLab. URL http://ilpubs.stanford.edu:8 0 90/3 8 6/

  12. Jsang A, Ismail R, Boyd C (2007) A survey of trust and reputation systems for online service provision. Decis Supp Syst 43(2):618–644. doi:http://dx.doi.org/10.1016/ j.dss.2005.05.019

    Article  Google Scholar 

  13. Kelleher T, Miller BM (2006) Organizational blogs and the human voice: relational strategies and relational outcomes. J Comput Med Commun 11(2):395–414

    Article  Google Scholar 

  14. Langville AN, Meyer CD (2006) Google’s pagerank and beyond: the science of search engine rankings. Princeton University Press, Princeton

    Book  Google Scholar 

  15. Page L, Brin S, Motwani R, Winograd T (1999) The pagerank citation ranking: bringing order to the web. Technical Report 1999-66, Stanford InfoLab. URL http://ilpubs.stanford.edu:8090/422/. Previous number = SIDL-WP-1999-0120

    Google Scholar 

  16. Peters R, Reitzenstein I (2008) Reputationssysteme im eCommerce-Funktionsweise, Anwendung und Nutzenpotenziale. HMD—Praxis der Wirtschaftsinformatik 45(261):43–50

    Article  Google Scholar 

  17. Resnick P, Zeckhauser R (2001) Trust among strangers in internet transactions: empirical analysis of ebay’s reputation system. Working paper for the NBER workshop on empirical studies of electronic commerce

    Google Scholar 

  18. Resnick P, Kuwabara K, Zeckhauser R, Friedman E (2008) Reputation systems. Commun ACM 43(12):45–48. doi:http://doi.acm.org/10.1145/355112.355122

    Article  Google Scholar 

  19. Schmidt FL, Hunter JE (1998) The validity and utility of selection methods in personnel psychology: practical and theoretical implications of 85 years of research findings. Psychol Bull 124(2):262–274

    Article  Google Scholar 

  20. Vossen G, Hagemann S (2007) Unleashing Web 2.0—from Concepts to Creativity. Morgan Kaufmann, San Francisco

    Google Scholar 

  21. Winkelmann A, Herwig S, Poppelbuß J, Tiebe D, Becker J (2009) Discussion of functional design options for online rating systems: a state-of-the-art analysis. In: Proceedings of the European conference on information systems. Verona, Italy

    Google Scholar 

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Correspondence to Till Haselmann .

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Haselmann, T., Winkelmann, A., Vossen, G. (2011). Towards a Conceptual Model for Trustworthy Skills Profiles in Online Social Networks. In: Pokorny, J., et al. Information Systems Development. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9790-6_23

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  • DOI: https://doi.org/10.1007/978-1-4419-9790-6_23

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-9645-9

  • Online ISBN: 978-1-4419-9790-6

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